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Paper Abstract and Keywords
Presentation 2023-05-23 11:40
NDVI prediction with SAR data using time series features
Raiki Kudo (UTokyo), Seiseke Fukuda (JAXA) SANE2023-7
Abstract (in Japanese) (See Japanese page) 
(in English) The Normalized Difference Vegetation Index (NDVI) is used to determine the growth of crops, the condition of cultivated land and forests, and land use.
NDVI is obtained from multispectral images acquired by optical satellites. However, accurate values cannot be obtained when light is blocked by clouds.
Research on estimating NDVI using data from Synthetic Aperture Radar (SAR) satellites, which use microwaves that penetrate clouds, is therefore attracting attention.
In this study, we focused on the time-series changes of vegetation and improved the accuracy of NDVI estimation by using the time-series changes of SAR images with short time scales and the characteristics of the time-series changes of vegetation over a year.
Experiments using satellite data confirmed the effectiveness of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Synthetic Aperture Radar / NDVI / Time Series / Random Forest / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 46, SANE2023-7, pp. 36-41, May 2023.
Paper # SANE2023-7 
Date of Issue 2023-05-16 (SANE) 
ISSN Online edition: ISSN 2432-6380
Copyright
and
reproduction		 All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SANE2023-7

Conference Information
Committee SANE  
Conference Date 2023-05-23 - 2023-05-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Information Technology R & D Center, MITSUBISHI Electric Corp. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Radar, EW and generals 
Paper Information
Registration To SANE 
Conference Code 2023-05-SANE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) NDVI prediction with SAR data using time series features 
Sub Title (in English)  
Keyword(1) Synthetic Aperture Radar  
Keyword(2) NDVI  
Keyword(3) Time Series  
Keyword(4) Random Forest  
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1st Author's Name Raiki Kudo  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Seiseke Fukuda  
2nd Author's Affiliation Japan Aerospace Exploration Agency (JAXA)
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Speaker Author-1 
Date Time 2023-05-23 11:40:00 
Presentation Time 20 minutes 
Registration for SANE 
Paper # SANE2023-7 
Volume (vol) vol.123 
Number (no) no.46 
Page pp.36-41 
#Pages 6 
Date of Issue 2023-05-16 (SANE) 

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